Identification of Plastic Properties From Conical Indentation Using a Bayesian-Type Statistical Approach Academic Article uri icon

abstract

  • The plastic properties that characterize the uniaxial stressstrain response of a plastically isotropic material are not uniquely related to the indentation force versus indentation depth response. We consider results for three sets of plastic material properties that give rise to essentially identical curves of indentation force versus indentation depth in conical indentation. The corresponding surface profiles after unloading are also calculated. These computed results are regarded as the experimental data. A simplified Bayesian-type statistical approach is used to identify the values of flow strength and strain hardening exponent for each of the three sets of material parameters. The effect of fluctuations (noise) superposed on the experimental data is also considered. We build the database for the Bayesian-type analysis using finite element calculations for a relatively coarse set of parameter values and use interpolation to refine the database. A good estimate of the uniaxial stressstrain response is obtained for each material both in the absence of fluctuations and in the presence of sufficiently small fluctuations. Since the indentation force versus indentation depth response for the three materials is nearly identical, the predicted uniaxial stressstrain response obtained using only surface profile data differs little from what is obtained using both indentation force versus indentation depth and surface profile data. The sensitivity of the representation of the predicted uniaxial stressstrain response to fluctuations increases with increasing strain hardening. We also explore the sensitivity of the predictions to the degree of database refinement.

published proceedings

  • JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME

altmetric score

  • 1

author list (cited authors)

  • Zhang, Y., Hart, J. D., & Needleman, A.

citation count

  • 12

complete list of authors

  • Zhang, Yupeng||Hart, Jeffrey D||Needleman, Alan

publication date

  • January 2019